Local news, though critical to quality information ecosystems, currently faces a crisis. Research shows that local news is rapidly disappearing, with a wide range of negative consequences for impacted communities. Exploring the local news crisis through a case study, this chapter presents a longitudinal analysis of local news at the New York Times and its distribution on Twitter. Our quantitative analysis characterizes (1) long-term trends in local news production, (2) shifts in curation when the Times introduced the “blossom” algorithm to support editorial decisions, and (3) shifts in audience engagement when Twitter implemented algorithmic timelines. Evidence suggests a constrained flow of local news: a steady decline in production, reduced sharing rates after the “blossom” algorithm was introduced, and reduced engagement after Twitter switched to algorithmic timelines. We conclude by discussing our results as evidence of a complex, multi-faceted local news crisis, and lay out potential points for intervention.